table-1-generator
Automated baseline characteristics table generation for clinical papers
57
3.66x
Quality
35%
Does it follow best practices?
Impact
99%
3.66xAverage score across 3 eval scenarios
Securityby
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Data analysis/table-1-generator-advanced/SKILL.mdTable 1 Generator
Automated generation of baseline characteristics tables (Table 1) for clinical research papers.
Usage
python scripts/main.py --data patients.csv --group treatment --output table1.csvParameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
--data | str | Yes | - | Patient data CSV file path |
--group | str | No | - | Grouping variable (e.g., treatment/control) |
--vars | list[str] | No | - | Variables to include in the table |
--output | str | Yes | - | Output file path for Table 1 |
Features
- Automatic variable type detection
- Appropriate statistics (mean±SD, median[IQR], n(%))
- Group comparisons (t-test, chi-square)
- Missing data reporting
- APA formatting
Output
- Table 1 (CSV/Excel)
- Statistical test results
- Formatted for publication
Risk Assessment
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
Security Checklist
- No hardcoded credentials or API keys
- No unauthorized file system access (../)
- Output does not expose sensitive information
- Prompt injection protections in place
- Input file paths validated (no ../ traversal)
- Output directory restricted to workspace
- Script execution in sandboxed environment
- Error messages sanitized (no stack traces exposed)
- Dependencies audited
Prerequisites
# Python dependencies
pip install -r requirements.txtEvaluation Criteria
Success Metrics
- Successfully executes main functionality
- Output meets quality standards
- Handles edge cases gracefully
- Performance is acceptable
Test Cases
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- Performance: Large dataset → Acceptable processing time
Lifecycle Status
- Current Stage: Draft
- Next Review Date: 2026-03-06
- Known Issues: None
- Planned Improvements:
- Performance optimization
- Additional feature support
- Repository
- aipoch/medical-research-skills
- Commit
ca9aaa4
- Last updated
- Created
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